Classifiers are used for a variety of applications in the software and hardware arts. For example, a classifier may be used to identify inappropriate emails, to identify unsolicited email (SPAM), to identify potential viruses, to project the performance or load of hardware and/or software resources, and the like. In some instances, a classifier may assign a probability to a given portion of input data, where that probability reflects a confidence factor that the given portion of input data belongs to a given classification. In this manner, an actual assignment to a given classification can be configured based on a certain probability value being exceeded, met, or not met. Probability assignments permit classifiers to be used in a variety of different automated decision making tasks where alternative choices may be made and where selections are made based on those choices which have higher probability assignments vis-à-vis other alternative choices. Consequently, classifiers may also be used and/or embedded within artificial intelligence applications and systems.
A classifier will include some degree of error, which means that the classifier does not always process perfectly against all types of input data and in all possible situations which may arise. Accordingly, classification errors can occur for a variety of reasons, such as new data previously not encountered by a classifier, new situations not encountered by the classifier, undetected logic errors included in the classifier, standard error margins associated with algorithms that are implemented within the classifier, etc.